Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_2405.vcf.gz --id UKB-b:2227 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2405.txt.gz --cohort_controls 209872 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2227/UKB-b-2227_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2227/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:22 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2227/UKB-b-2227_data.vcf.gz ...
Read summary statistics for 9531338 SNPs.
Dropped 11874 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1288433 SNPs remain.
After merging with regression SNP LD, 1288433 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0348 (0.0028)
Lambda GC: 1.1512
Mean Chi^2: 1.1599
Intercept: 1.017 (0.0065)
Ratio: 0.1061 (0.0407)
Analysis finished at Thu Oct 17 14:43:54 2019
Total time elapsed: 1.0m:32.59s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9492,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -8.4838e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 3,
    "n_p_sig": 503,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 137389,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1288433,
    "ldsc_nsnp_merge_regression_ld": 1288433,
    "ldsc_observed_scale_h2_beta": 0.0348,
    "ldsc_observed_scale_h2_se": 0.0028,
    "ldsc_intercept_beta": 1.017,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.1512,
    "ldsc_mean_chisq": 1.1599,
    "ldsc_ratio": 0.1063
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9519525 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9531338 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.628548e+00 5.751368e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.883335e+07 5.630543e+07 828.0000000 3.254068e+07 6.942201e+07 1.145672e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -8.500000e-06 1.037200e-02 -0.1366300 -3.638600e-03 -6.900000e-06 3.614500e-03 1.534110e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.796400e-03 6.597500e-03 0.0024394 2.956600e-03 4.785600e-03 1.059200e-02 8.248090e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.841984e-01 2.928861e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.841992e-01 2.928616e-01 0.0000000 2.267554e-01 4.788140e-01 7.377810e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.092141e-01 2.572528e-01 0.0016680 1.553000e-02 8.606700e-02 3.273078e-01 9.983320e-01 ▇▂▁▁▁
numeric AF_reference 137389 0.9855855 NA NA NA NA NA NA NA 2.110175e-01 2.489639e-01 0.0000000 1.317890e-02 1.058310e-01 3.286740e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0058735 0.0044880 0.1900002 0.1906359 0.624255 0.7821490 NA
1 54676 rs2462492 C T 0.0074814 0.0044574 0.0929994 0.0932647 0.399771 NA NA
1 86028 rs114608975 T C -0.0049513 0.0070999 0.4899999 0.4855729 0.103630 0.0277556 NA
1 91536 rs6702460 G T 0.0050088 0.0043852 0.2500000 0.2533634 0.456579 0.4207270 NA
1 234313 rs8179466 C T -0.0088024 0.0086298 0.3100002 0.3077288 0.074583 NA NA
1 534192 rs6680723 C T -0.0083246 0.0050063 0.0959997 0.0963479 0.240668 NA NA
1 546697 rs12025928 A G -0.0048466 0.0062470 0.4400003 0.4378554 0.913408 NA NA
1 693731 rs12238997 A G -0.0053578 0.0041995 0.2000000 0.2020154 0.115958 0.1417730 NA
1 705882 rs72631875 G A -0.0052050 0.0061448 0.4000000 0.3969573 0.067476 0.0315495 NA
1 706368 rs55727773 A G 0.0040432 0.0031090 0.1900002 0.1934382 0.516227 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0094078 0.0065139 0.1499999 0.1486650 0.042052 0.0473243 NA
22 51219766 rs182321900 C T 0.0007365 0.0298598 0.9800000 0.9803216 0.001995 NA NA
22 51220146 rs868950473 C T 0.0030022 0.0295750 0.9199999 0.9191442 0.002052 NA NA
22 51221190 rs369304721 G A -0.0045901 0.0064974 0.4799997 0.4799096 0.049867 NA NA
22 51221731 rs115055839 T C -0.0070993 0.0048648 0.1400000 0.1444751 0.073304 0.0625000 NA
22 51222100 rs114553188 G T -0.0009580 0.0057385 0.8700001 0.8674214 0.054233 0.0880591 NA
22 51223637 rs375798137 G A -0.0009680 0.0057668 0.8700001 0.8666974 0.053853 0.0788738 NA
22 51229805 rs9616985 T C -0.0072376 0.0048829 0.1400000 0.1382759 0.073099 0.0730831 NA
22 51232488 rs376461333 A G -0.0047684 0.0115153 0.6800001 0.6788082 0.020025 NA NA
22 51237063 rs3896457 T C 0.0020333 0.0029900 0.5000000 0.4964882 0.298103 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624255 ES:SE:LP:AF:ID  0.00587346:0.00448801:0.721246:0.624255:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399771 ES:SE:LP:AF:ID  0.0074814:0.0044574:1.03152:0.399771:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10363  ES:SE:LP:AF:ID  -0.00495126:0.00709993:0.309804:0.10363:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456579 ES:SE:LP:AF:ID  0.00500882:0.00438517:0.60206:0.456579:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074583 ES:SE:LP:AF:ID  -0.00880236:0.00862977:0.508638:0.074583:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240668 ES:SE:LP:AF:ID  -0.00832464:0.00500633:1.01773:0.240668:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913408 ES:SE:LP:AF:ID  -0.00484657:0.00624703:0.356547:0.913408:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.115958 ES:SE:LP:AF:ID  -0.0053578:0.00419946:0.69897:0.115958:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067476 ES:SE:LP:AF:ID  -0.00520502:0.00614475:0.39794:0.067476:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516227 ES:SE:LP:AF:ID  0.00404319:0.00310901:0.721246:0.516227:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033112 ES:SE:LP:AF:ID  0.00438364:0.00782324:0.236572:0.033112:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036774 ES:SE:LP:AF:ID  0.00508728:0.00709901:0.327902:0.036774:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036895 ES:SE:LP:AF:ID  0.00490171:0.00707102:0.309804:0.036895:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03661  ES:SE:LP:AF:ID  0.00503054:0.00711968:0.318759:0.03661:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016459 ES:SE:LP:AF:ID  -0.0106024:0.0109816:0.481486:0.016459:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037156 ES:SE:LP:AF:ID  0.00536647:0.00704074:0.346787:0.037156:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037255 ES:SE:LP:AF:ID  0.00481014:0.00701616:0.309804:0.037255:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101382 ES:SE:LP:AF:ID  -0.00196056:0.00512286:0.154902:0.101382:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958893 ES:SE:LP:AF:ID  -0.00805934:0.00676786:0.638272:0.958893:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031477 ES:SE:LP:AF:ID  0.0172079:0.0123602:0.79588:0.031477:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053089 ES:SE:LP:AF:ID  0.0113785:0.00983087:0.60206:0.053089:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036744 ES:SE:LP:AF:ID  0.0051703:0.0070665:0.337242:0.036744:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037051 ES:SE:LP:AF:ID  0.00427846:0.00700164:0.267606:0.037051:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84339  ES:SE:LP:AF:ID  0.000992982:0.00363438:0.107905:0.84339:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055848 ES:SE:LP:AF:ID  -0.00620418:0.00588684:0.537602:0.055848:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12193  ES:SE:LP:AF:ID  -0.00355832:0.00398408:0.431798:0.12193:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025897 ES:SE:LP:AF:ID  -0.00109049:0.00975064:0.0409586:0.025897:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121197 ES:SE:LP:AF:ID  -0.00405211:0.00398572:0.508638:0.121197:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132063 ES:SE:LP:AF:ID  -0.00158395:0.00392632:0.161151:0.132063:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011137 ES:SE:LP:AF:ID  0.0110406:0.0142615:0.356547:0.011137:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005625 ES:SE:LP:AF:ID  0.00882094:0.0185986:0.19382:0.005625:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002306 ES:SE:LP:AF:ID  0.0660746:0.0306687:1.50864:0.002306:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036968 ES:SE:LP:AF:ID  0.00422442:0.00693016:0.267606:0.036968:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839183 ES:SE:LP:AF:ID  0.000959059:0.00352182:0.102373:0.839183:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838814 ES:SE:LP:AF:ID  0.00100127:0.00351765:0.107905:0.838814:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.87013  ES:SE:LP:AF:ID  0.00179413:0.0037781:0.200659:0.87013:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129516 ES:SE:LP:AF:ID  -0.00280382:0.00378494:0.337242:0.129516:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  0.0037743:0.00680905:0.236572:0.037527:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037747 ES:SE:LP:AF:ID  0.00334828:0.00676898:0.207608:0.037747:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869482 ES:SE:LP:AF:ID  0.00174768:0.00377012:0.19382:0.869482:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86961  ES:SE:LP:AF:ID  0.00177781:0.00377183:0.19382:0.86961:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03772  ES:SE:LP:AF:ID  0.00335979:0.00679707:0.207608:0.03772:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869487 ES:SE:LP:AF:ID  0.00180002:0.00377011:0.200659:0.869487:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005173 ES:SE:LP:AF:ID  0.0124607:0.0192116:0.283997:0.005173:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005135 ES:SE:LP:AF:ID  0.0128384:0.0192677:0.29243:0.005135:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838267 ES:SE:LP:AF:ID  0.000828901:0.00350801:0.091515:0.838267:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037733 ES:SE:LP:AF:ID  0.00333737:0.00680586:0.207608:0.037733:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838892 ES:SE:LP:AF:ID  0.000787245:0.00351786:0.0861861:0.838892:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013678 ES:SE:LP:AF:ID  -0.00288415:0.0123219:0.091515:0.013678:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005523 ES:SE:LP:AF:ID  0.00378131:0.0189768:0.0757207:0.005523:rs184270342